Test and measurement instrument including asynchronous time-interleaved digitizer using harmonic mixing and a linear time-periodic filter

ABSTRACT

A test and measurement instrument, including a splitter configured to split an input signal having a particular bandwidth into a plurality of split signals, each split signal including substantially the entire bandwidth of the input signal, a plurality of harmonic mixers, each harmonic mixer configured to mix an associated split signal of the plurality of split signals with an associated harmonic signal to generate an associated mixed signal, a plurality of digitizers, each digitizer configured to digitize a mixed signal of an associated harmonic mixer of the plurality of harmonic mixers, and a linear time-periodic filter configured to receive the digitized mixed signal from each of the digitizers and output a time-interleaved signal. A first-order harmonic of at least one harmonic signal associated with the harmonic mixers is different from a sample rate of at least one of the digitizers.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/347,600, filed Nov. 9, 2016, which is a continuation of U.S. patentapplication Ser. No. 14/851,937, filed Sep. 11, 2015, issued as U.S.Pat. No. 9,525,427, each of which are hereby incorporated by referenceinto this application in their entirety.

TECHNICAL FIELD

This invention relates to test and measurement instruments and, moreparticularly, to test and measurement instruments including one or moreasynchronous time-interleaved digitizers, which use harmonic mixing forreducing noise.

BACKGROUND

Useable bandwidths of test and measurement instruments, such as digitaloscilloscopes, can be limited by an analog to digital converter (ADC)used to digitize input signals. The useable bandwidth of an ADC can belimited to the lesser of the analog bandwidth or one half of a maximumsample rate of the ADC. Various techniques have been developed todigitize higher bandwidth signals with existing ADCs.

For example, synchronous time-interleaving can be used to achieve aneffective higher sample rate. Multiple ADCs can sample an input signaloffset in time within a single sample period. The digitized outputs canbe combined together for an effectively multiplied sample rate. However,if the analog bandwidth of the ADCs becomes the limiting factor, a highbandwidth front end, such as a multi-way interleaved track and holdamplifier is needed to achieve a higher bandwidth.

Conventional track and hold amplifier-based time-interleaved systemscause the track and hold amplifier to be clocked at a sample ratesimilar to or slower than the ADC channel bandwidth so that the ADC willhave sufficient time to settle to the held value. The ADC issynchronously clocked to the track and hold amplifier to digitallycapture each held value. Such a limitation on the track and holdamplifier in turn limits the ADC sample rate. Moreover, to satisfy theNyquist sampling theorem, the ADC sample rate is lowered to less thantwice the bandwidth of the ADC channel. As a result, manytime-interleaved ADC channels are needed to achieve the desiredperformance.

As the number of ADC channels increases, the overall cost and complexityof the system also increases. For instance, the front end chip must nowdrive more ADC channels, including additional ADC circuitry, clockingcircuitry, or the like, to get the overall net sample rate up to asuitable value. The size and complexity of the chip also results inlonger communication paths, and therefore, an increase in parasiticcapacitance, electromagnetic noise, design difficulties, and so forth.

In another technique, sub-bands of an input signal can be downconvertedto a frequency range that can be passed through a lower sample rate ADC.In other words, the wide input bandwidth can be split into multiplelower-bandwidth ADC channels. After digitization, the sub-bands can bedigitally upconverted to the respective original frequency ranges andcombined into a representation of the input signal. One significantdisadvantage of this technique is the inherent noise penalty whendigitizing an arbitrary input signal whose frequency content may berouted to only one ADC channel. The recombined output will containsignal energy from only one ADC, but noise energy from all ADCs, therebydegrading the Signal-to-Noise Ratio (SNR).

Accordingly, a need remains for improved devices and methods fordigitizing any frequency input signal by all ADC channels in anasynchronous time-interleaved architecture, thereby avoiding the noisepenalty.

U.S. Pat. No. 8,742,749, titled TEST AND MEASUREMENT INSTRUMENTINCLUDING ASYNCHRONOUS TIME-INTERLEAVED DIGITIZER USING HARMONIC MIXING,issued Jun. 3, 2014, incorporated by reference herein in its entirety,discusses an asynchronous time-interleaved system with a reconstructionalgorithm to reconstruct the signal after the signal has been split andprocessed.

SUMMARY

Embodiments of the disclosed technology are directed to a test andmeasurement instrument, including a splitter configured to split aninput signal having a particular bandwidth into a plurality of splitsignals, each split signal including substantially the entire bandwidthof the input signal; a plurality of harmonic mixers, each harmonic mixerconfigured to mix an associated split signal of the plurality of splitsignals with an associated harmonic signal to generate an associatedmixed signal; a plurality of digitizers, each digitizer configured todigitize a mixed signal of an associated harmonic mixer of the pluralityof harmonic mixers; and a linear time-periodic filter configured toreceive the digitized mixed signal from each of the digitizers andoutput a time-interleaved signal. A first-order harmonic of at least oneharmonic signal associated with the harmonic mixers is different from aneffective sample rate of at least one of the digitizers.

Embodiments of the disclosed technology are also directed to a methodincluding splitting an input signal having a particular bandwidth into aplurality of split signals, each split signal including substantiallythe entire bandwidth of the input signal; mixing each split signal withan associated harmonic signal to generate an associated mixed signal;digitizing each mixed signal; receiving the digitized mixed signal fromeach of the digitizers at a linear time-periodic filter; and outputtinga time-interleaved signal from the linear time-periodic filter. Afirst-order harmonic of at least one harmonic signal associated with theharmonic mixers is different from a sample rate of at least one of thedigitizers

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an ADC system for a test and measurementinstrument using harmonic mixing.

FIG. 2 is a block diagram of an ADC system for a test and measurementinstrument using harmonic mixing according to some embodiments of thedisclosed technology.

DETAILED DESCRIPTION

FIG. 1 is a block diagram of an ADC system for a test and measurementinstrument using harmonic mixing. In this embodiment, the instrumentincludes a splitter 10 configured to split an input signal 12 having aparticular frequency spectrum into multiple split signals 14 and 16,each split signal including substantially the entire spectrum of theinput signal 12. A splitter 10 can be any variety of circuitry that cansplit the input signal 12 into multiple signals. For example, thesplitter 10 can be a resistive divider. Thus, substantially allfrequency components of the input signal 12 can be present in each splitsignal 14 and 16. However, depending on the number of paths, harmonicsignals used, or the like, the frequency responses for various splitsignals of a splitter 10 can be different.

The split signals 14 and 16 are inputs to harmonic mixers 18 and 24,respectively. Harmonic mixer 18 is configured to mix the split signal 14with a harmonic signal 20 to generate a mixed signal 22. Similarly,harmonic mixer 24 is configured to mix the split signal 16 with aharmonic signal 26 to generate a mixed signal 28.

As used herein, a harmonic mixer is a device configured to mix a signalwith multiple harmonics. Although multiplication and/or mixing has beendescribed in connection with harmonic mixing, a device that has theeffect of multiplying a signal with multiple harmonics can be used as aharmonic mixer.

A digitizer 30 is configured to digitize mixed signal 22. Similarly, adigitizer 32 is configured to digitize mixed signal 28. The digitizers30 and 32 can be any variety of digitizer. Although not illustrated,each digitizer 30 and 32 can have a preamplifier, filter, attenuator,and other analog circuitry as needed. Thus, the mixed signal 22 input tothe digitizer 30, for example, can be amplified, attenuated, orotherwise filtered before digitization.

The digitizers 30 and 32 are configured to operate at an effectivesample rate. The effective sample rate is a rate that allows thedigitizers 30 and 32 to adequately digitize the signals 22 and 28, andmay be chosen, for example, to optimize the signal-to-noise ratio withinthe frequency band of interest within signals 22 and 28. In someembodiments, the digitizer 30 can include a single analog to digitalconverter (ADC). However, in other embodiments, the digitizer 30 caninclude multiple interleaved ADCs operating at lower sample rates toachieve a higher effective sample rate.

A first-order harmonic of at least one of the harmonic signals 20 and 26is different from an effective sample rate of at least one of thedigitizers 30 and 32. In some embodiments, the first-order harmonic of aharmonic signal need not be an integer multiple or sub-multiple of theeffective sample rate of the at least one of the digitizers. In otherwords, in some embodiments, the first-order harmonic of a harmonicsignal associated with the harmonic mixers is not an integer multiple orsub-multiple of the effective sample rate of the at least one of thedigitizers.

It should be understood that all bands of the input signal 12 go throughall paths. In other words, when more than one channel is combined forprocessing a single input signal 12, each channel or path receivessubstantially the entire bandwidth of the input signal 12. As the inputsignal 12 is transmitted through all of the digitizers, the signal tonoise ratio is significantly improved.

A filter 36 can be configured to filter the digitized mixed signal 34from digitizer 30. Similarly, a filter 42 can be configured to filterthe mixed signal 40 from digitizer 32. Filters 36 and 42 may be, forexample, equalization and interpolation filters. Harmonic mixers 46 and52 are configured to mix the filtered mixed signals 38 and 44 withharmonic signals 48 and 54, respectively. In some embodiments, theharmonic signals 48 and 54 can be substantially similar in frequency andphase to the corresponding harmonic signals 20 and 26. While theharmonic signals 20 and 26 are analog signals, and the harmonic signals48 and 54 are digital signals, the scaling factors for these harmonicsignals can be the same or similar to each other. The output signals 50and 56 are referred to as remixed signals 50 and 56. A combiner 58 isconfigured to combine the remixed signals 50 and 56 into a reconstructedinput signal 60. In some embodiments, the combiner 58 can implement morethan mere addition of signals. For example, averaging, filtering,scaling, or the like can be implemented in the combiner 58. That is, thecombiner 58 may include a low-pass filter (LPF) 62 or the LPF 62 may beplaced outside the combiner, as shown in FIG. 1.

The filters 36 and 42, the harmonic mixers 46 and 52, harmonic signals48 and 54, the combiner 58, and other associated elements can beimplemented digitally. For example, a digital signal processor (DSP),microprocessor, programmable logic device, general purpose processor, orother processing system with appropriate peripheral devices as desiredcan be used to implement the functionality of the processing of thedigitized signals. Any variation between complete integration to fullydiscrete components can be used to implement the functionality.

For example, some filtering can occur prior to digitization. The mixedsignals 22 and 28 could be filtered with a low pass filter having acutoff frequency near one half of the effective sample rate of thedigitizers 30 and 32. The filtering of filters 36 and 42 can add to suchinherent and/or induced filtering.

In some embodiments, the net filtering of the mixed signals 22 and 28can result in a frequency response that is substantially complementaryabout one half of a frequency of the first-order harmonic of theharmonic signals 20 and 26. That is, the frequency response at a givenoffset higher than frequency F₁/2 and the frequency response at a givenoffset lower than frequency F₁/2 can add to one. Although one has beenused as an example, other values can be used as desired, such as forscaling of signals. Furthermore, the above example is described as anideal case. That is, the implemented filtering can have differentresponse to account for non-ideal components, calibration, or the like.

In the event of interleaving errors due to analog mismatch, hardwareadjustments can be made for mixing clock amplitude and phase. Theadjustments can then be calibrated to minimize interleave mismatchspurs. Alternatively, or in addition to the above approach, hardwaremismatches can be characterized, and a linear, time-varying correctionfilter 64 may be used to cancel the interleave spurs.

Moreover, although the digital filtering, mixing, and combining havebeen described as discrete operations, such operations can be combined,incorporated into other functions, or the like. In addition, as theabove discussion assumed ideal components, additional compensation, canbe introduced into such processing as appropriate to correct fornon-ideal components. Furthermore, when processing the digitizedsignals, changing frequency ranges, mixing, and the like can result in ahigher sample rate to represent such changes. The digitized signals canbe upsampled, interpolated, or the like as appropriate.

A memory 66 may be provided between digitizer 30 and filter 36 in theupper ADC channel and a memory 68 between digitizer 32 and filter 42 inthe lower ADC channel. An acquisition can be performed and the digitizedmixed signal 34 or the digitized mixed signal 40 can be stored inmemories 66 and 68, respectively, before being sent to filters 36 and42, respectively.

As discussed above, the reconstruction appliesequalization/interpolation filters 36 and 42 to the ADC data streams,mixes them with a digital version of the harmonic mixing function viaharmonic mixers 46 and 52, averages the results via combiner 58,low-pass filters 62 the averaged results to remove upper mixingproducts, and then applies a linear, time-varying correction filter 64.All of these steps are linear operators, i.e. for any scalars a and band input signals x(t) and y(t),

F{a·x(t)+b·y(t)}=a·F{x(t)}+b·F{y(t)}  (1)

Since digital signal processors are used, time is represented indiscrete time intervals, represented by an integer value “t,” where eachincrement oft represents one sample point of time. The sample intervalbetween adjacent points in time, for example, may be 5 ps. However, anyother sample interval may be used.

The equalization/interpolation filters 36 and 42 and low-pass filter 62are time-invariant as well as linear, i.e.,

F{x(t−t ₀)}=F{x(t)}|t−t ₀  (2)

The variable to is any arbitrary integer time delay. These filters willbe referred to herein as linear time-invariant (LTI) filters. An LTIfilter can be fully and uniquely represented by its impulse response,and a cascade of LTI filter components is also an LTI filter, with animpulse response equal to the convolution of the components' impulseresponses.

The mixing functions 48 and 54 and linear, time-varying correctionfilter 64 vary over time. However, if the mixing frequency isharmonically related to the underlying ADC interleaving rate, both stepswill be time-periodic, i.e.,

F{x(t−kT)}=F{x(t)}|t−kT  (3)

The variable k is any integer and T is the least common period of themixing function and the interleave rate. These are referred to aslinear, time-periodic filters (“LTP”). For example, the mixing functionmay be 75 GHz, the interleave rate is 12.5 GS/s, and T=16, which at 5 psper sample point represents 80 ps. The mixing function is being viewedas a filter with a single coefficient, one point duration impulseresponse, which varies periodically over time (completing six cycles in16 samples in this example).

LTI filters may be a subclass of LTP filter by letting to =kT. Thus, thereconstruction may be represented as a cascade of LTP filters.

An LTP filter can be fully and uniquely represented by an array of Timpulse responses, where T is the integer period of the LTP filter.Array entry 0 equals the response of the filter to an impulse at timet=0, array entry 1 equals the response of the filter to an impulse attime t=1 advanced by one sample, array entry 2 equals the response ofthe filter to an impulse at time t=2 advanced by two samples, etc. Notethat if an array entry is defined at T, it would be the response of thefilter to an impulse at the time t=T advanced by T samples, but by theperiodicity property that is identical to the response of an impulse att=0, which is already stored in array entry 0. Hence, the array of Timpulse responses defines the response to an impulse at any time, and bylinearity, the response to any signal (represented as a linearcombination of impulses at different times) can be determined. An LTIfilter, as a subclass of LTP filters of period T, would be representedby having all T entries identical.

An LTP filter response of duration N samples can be stored as atwo-dimensional T by N array, indexed by the input impulse location(modulo T) and the output sample. For simplicity of notation, let boldfont represent modulo T, i.e.,

i=i(modulo T)  (4)

Then, the output y(t) of an LTP filter “f” can be expressed in terms ofits input x(t) akin to a convolution:

y(t)=x(t)*f=Σ _(i) x(i)·f(i,t−i)  (5)

Likewise, the output y(t) of a cascade of two LTP filters “f” and “g”can be expressed in terms of its input x(t):

y(t)=[x(t)*f]*g=Σ _(j)[Σ_(i) x(i)·f(i,j−i)]·g(j,t−j)=Σ_(i) x(i)·[Σ_(j)f(i,j−i)·g(j,t−j)]=Σ_(i) x(i)·{f*g}(i,t−  (6)

Where {f*g}(i,m) is defined as:

{f*g}(i,m)=Σ_(k) f(i,k)·g(i+k,m−k)  (7)

Thus, the “periodic convolution” of LTP filters f and g can bepre-calculated, the result can be stored as LTP filter f*g, and theinput x can be convolved with this new filter to calculate the output y.In a similar fashion, the “periodic convolution” of any number of LTPfilters (such as all the steps of the reconstruction algorithm) may bepre-calculated and just one LTP filter may be applied to the data atruntime.

The “periodic convolution” of LTP filters follows the associative rule,as does the convolution of LTI filters, as shown in equation (8):

(f*g)*h=f*(g*h)  (8)

However, the communicative rule does not apply to LPT filters as it doesto LTI filters. That is, equation (9) applies to LTI filters, but notnecessarily to LTP filters:

f*g=g*f  (9)

The first step of reconstruction applies an equalization andinterpolation filter 36 or 42 to each ADC channel's data stream. Theoutput rate of the equalization and interpolation filters 36 and 42 isgenerally N times the input rate (where N is the number of interleaveddigitizers), and this is often viewed as a two-step process: insertingN−1 zero samples between the ADC samples to achieve N times the datarate, then applying a low-pass LTI filter at the higher rate to removethe aliased energy created by the alternating samples and zeroes. Whenrepresenting this loss-pass filter as an LTP filter, though, N−1 of Nentries in the array of T impulse responses can be set to zero, sorather than inserting zero samples to increase the rate, any arbitrarysamples may be inserted since they will subsequently get multiplied by azero impulse response. For example, the ADC samples from the other N−1ADC channel(s) may be inserted.

This approach can be used for all equalization and interpolation filters36 and 42, choosing the non-zero rows in each array to correspond withthe associated digitizer's samples. This allows the same interleaveddata stream, containing interleaved samples from all ADC channels, to befed into all equalization and interpolation filters 36 and 42, and bylinearity, the N resultant LTP filters representing the N paths may beadded to obtain a single LTP filter to output a reconstructed datastream. The whole reconstruction process then may become applying asingle LTP filter to the ADC data, taken as an interleaved stream.

As when convolving LTI filters, the duration of the response of severalconvolved LTP filters will generally be the sum of the durations of thecomponent filters, minus the number of filters convolved, plus one.However, the filter coefficients near either end are likely to be verysmall, both because there are fewer non-zero terms to add together inthe summation and because those terms that do get added are the productof coefficients from near the end of the component filter responses,which tend to be small, making their product “small squared” or verysmall. Thus, the duration of the final convolved LTP filter may bepractically limited to something less than the theoretical combinationsdiscussed above, saving even more execution time. In some embodiments,applying a smooth windowing function may be useful to avoid an abrupttruncation of the response.

This allows the entire reconstruction algorithm to be reduced to anapplication of a single LTP filter to the interleaved ADC data stream,thus reducing processing time and allowing faster update rates at longrecord lengths. That is, an LTP system may be defined as a cascade ofLTP filters and be characterized as a single LTP filter by use ofperiodic convolution. Alternatively, any algorithm that is known to belinear and time-periodic, i.e., is an LTP system, may be characterizedas a single LTP filter by application of the algorithm to T inputrecords, where each input record is an impulse at location t, where0≤t<T. This technique directly measures the impulse responses which,after advancing by t samples, are stored in the impulse response arrayof the single LTP filter. This direct determination of the systemimpulse response array can be applied to any LTP system, even ifimplemented inside a “black-box” wherein the operation of the algorithmcannot be directly observed. For example, this approach of directlydetermining the impulse response can be used with a system in a“black-box” whether that system internally operates as a cascade of LTPcomponents or uses some other processing technique, e.g., frequencydomain analysis.

Pre-calculation of the LTP system impulse response array will take time,whether done using periodic convolutions of the components or applyingthe black-box measurement approach. The execution time savings, then,comes from assuming that the duration of the record(s) to bereconstructed by one LTP filter are long compared to the duration of theLTP system response. This assumption is often valid, as the recordlengths may go into the millions of samples, whereas the system responseduration is in the hundreds of samples.

However, if a user requests shorter records and triggers them far enoughapart to require recalculating the LTP filter to account for hardwaredrift, it may be faster to apply each LTP component to the data recordin cascade. On the other hand, processing throughput may not be an issuein this case with short records and slow triggers.

After reconstruction, a band width enhancement (BWE) filter 70 may beapplied using a much longer duration LTI filter using frequency domaintechniques. If this filter is much longer in duration than any of theLTP filters, it may be kept separate. Treating the BWE filter 70 as partof the LTP cascade, though mathematically accurate, would requirecalculating T (16 in the examples above) long-duration responses whichwould complicate and potentially slow the frequency-domain filteringtechnique in use. The periodic convolution technique applies best whenincorporating LTI filter durations less than or comparable to thelongest inherently time varying filter duration.

FIG. 2 illustrates the filters 36 and 42, harmonic mixers 46 and 52,combiner 58, low-pass filter 62, and linear-time varying filter 64 as asingle convolved LTP filter 72. That is, the output from the digitizer30 and digitizer 32 may be inputted directly into the LTP filter 72,rather than through each of the components shown in FIG. 1. The LTPfilter 72 outputs reconstructed interleaved signal.

Although FIG. 2 illustrates the filters 36 and 42, harmonic mixers 46and 52, combiner 58, low-pass filter 62, and linear-time varying filter64 as being convolved into a single LTP filter 72, multiple LTP filtersmay be used instead of a single LTP filter. Alternatively, LTP filter 72may include two or more of filters 36 and 42, harmonic mixers 46 and 52,combiner 58, low-pass filter 62, and linear-time varying filter 64,while the filters not convolved remain.

Another embodiment includes computer readable code embodied on acomputer readable medium that when executed, causes the computer toperform any of the above-described operations. As used here, a computeris any device that can execute code. Microprocessors, programmable logicdevices, multiprocessor systems, digital signal processors, personalcomputers, or the like are all examples of such a computer. In someembodiments, the computer readable medium can be a tangible computerreadable medium that is configured to store the computer readable codein a non-transitory manner.

Although particular embodiments have been described, it will beappreciated that the principles of the invention are not limited tothose embodiments. Variations and modifications may be made withoutdeparting from the principles of the invention as set forth in thefollowing claims. For example, it is anticipated that a re-ordering ofthe digital filtering, mixing, and/or combining may allow for moreefficient execution of the digital processing while still providing forreconstruction of a digital representation of the input signal.

What is claimed is:
 1. A method, comprising: measuring a plurality of Timpulse responses of a linear time-periodic filter; storing the measuredplurality of impulse responses in a memory as an array h of size T, inwhich the array entry h[t] equals the response of the filter at a timet, and in which h[0]=h[T].
 2. The method of claim 1, further comprisingconvolving the array h with an input signal to produce an output signal,in which the input signal results from digitization of a harmonicallymixed signal, the digitization using a sample rate that is not amultiple or sub-multiple of a harmonic signal used to produce theharmonically mixed signal.